Style translation filter to change attribute of motion

Akihiko Yamaguchi, Shiori Sato, Kentaro Takemura, Jun Takamatsu, Tsukasa Ogasawara

研究成果: Conference contribution

抄録

In this paper, we propose a style translation filter that changes the attribute (style) of the motion coming from the actors' ages, genders, and so on. Using this filter, we can diversify the motions. Specifically, this filter is modeled by the Gaussian process regression that estimates the difference of pose (joint angles) between a neutral motion and the motion of a target attribute. In learning this filter, a key technique is to find pairs of corresponding posed from the sample motions. We solve this problem by employing the Multifactor Gaussian Process Model (MGPM) proposed by Wang et al. [1]. In the experiments, we constructed multiple style translation filters from several attributes of walking motions, such as genders, ages, and emotions. The obtained filters were applied to some kinds of testing motions, such as walking, jumping, kicking, and dancing. The acquired motions were verified by a questionnaire study; the most of their attributes were changed to the filters' target attributes.

本文言語English
ホスト出版物のタイトル2012 12th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2012
ページ660-665
ページ数6
DOI
出版ステータスPublished - 2012 12 1
外部発表はい
イベント2012 12th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2012 - Osaka, Japan
継続期間: 2012 11 292012 12 1

出版物シリーズ

名前IEEE-RAS International Conference on Humanoid Robots
ISSN(印刷版)2164-0572
ISSN(電子版)2164-0580

Other

Other2012 12th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2012
CountryJapan
CityOsaka
Period12/11/2912/12/1

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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